DocumentCode
2519261
Title
Research on test paper auto-generating based on immune genetic algorithm
Author
Yan-cong, Zhou ; Jun-hua, Gu ; Xiao-chen, Sun ; Yong-feng, Dong ; Ming, Fan
Author_Institution
Tianjin Univ. of Commerce, Hebei Univ. of Technol., Tianjin, China
fYear
2011
fDate
23-25 May 2011
Firstpage
2498
Lastpage
2502
Abstract
In order to improve the auto-generating test paper´s quality at the cost of low time, an intelligent algorithm based on immune genetic algorithm was proposed. In the algorithm immune process was added into the basic framework of genetic algorithm, and the algorithm based on vaccination was put forward and used for test paper auto-generating. The problem that genetic algorithm is precocity and easy to fall into a local optimization was resolved by this algorithm. The feasibility and validity of the algorithm was proved by test data compared with other algorithms. At last the validating system enhances the users´ condition constraints for test paper through manual inching, thus the system is more simple and practical.
Keywords
educational administrative data processing; genetic algorithms; auto-generating test paper quality; immune genetic algorithm; intelligent algorithm; manual inching; Computers; Convergence; Databases; Genetic algorithms; Optimization; Testing; Vaccines; Genetic algorithm; Immune algorithm; Local convergence; Test paper auto-generating; Vaccination;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (CCDC), 2011 Chinese
Conference_Location
Mianyang
Print_ISBN
978-1-4244-8737-0
Type
conf
DOI
10.1109/CCDC.2011.5968629
Filename
5968629
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